• 제목/요약/키워드: nonparametric detection

검색결과 47건 처리시간 0.019초

First Order Difference-Based Error Variance Estimator in Nonparametric Regression with a Single Outlier

  • Park, Chun-Gun
    • Communications for Statistical Applications and Methods
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    • 제19권3호
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    • pp.333-344
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    • 2012
  • We consider some statistical properties of the first order difference-based error variance estimator in nonparametric regression models with a single outlier. So far under an outlier(s) such difference-based estimators has been rarely discussed. We propose the first order difference-based estimator using the leave-one-out method to detect a single outlier and simulate the outlier detection in a nonparametric regression model with the single outlier. Moreover, the outlier detection works well. The results are promising even in nonparametric regression models with many outliers using some difference based estimators.

오일러 수와 구조 텐서를 사용한 개선된 Nonparametric 변화 검출 알고리즘 (An Improved Nonparametric Change Detection Algorithm Using Euler Number and Structure Tensor)

  • 이웅희;김태희;정동석
    • 한국통신학회논문지
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    • 제28권10C호
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    • pp.958-966
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    • 2003
  • 동영상에서 움직이는 객체를 찾아내기 위해 프레임 차분에 기반을 둔 변화 검출 알고리즘이 많이 사용된다. 이러한 알고리즘들은 프레임의 변화를 추정된 통계적 배경 모델을 이용하여 검출한다. 그러나 이러한 추정된 배경 모델이 실제 통계적 분포와 다르면 잘못된 검출 결과들이 생성되게 된다. 본 논문에서는 오일러 수와 구조적 텐서를 이용한 개선된 변화 검출 알고리즘을 제안한다. 제안된 오일러 수에 기반을 둔 맵핑 방법은 Nonparametric 변화검출 알고리즘에 의해 잘못 검출된 결과를 감소시키는데 사용될 수 있다. 또한 본 논문에서 제안된 구조 텐서를 이용한 방법은 움직인 객체 영역 내부의 변화를 검출하는데 사용된다. 제안된 방법은 기존의 방법에 비해 Weather에서는 90%, Mother & daughter에서는 34% 그리고 Aisle에서는 43%의 검출 에러 감소 효과를 얻을 수 있음을 실험 결과로 확인한다.

덧셈 잡음에서 합성신호의 비모수 검파기 (A nonparametric detection scheme of composite signals in additive noise)

  • 배진수;박주식;김윤희;송익호
    • 한국통신학회논문지
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    • 제22권7호
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    • pp.1543-1549
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    • 1997
  • In this paper, rank-based nonparmetric detection of composite signals in additive noise is considered. Based on signs and ranks of observations, the locally optimum detector is deived for weak-signal detection under any specified noise probability density funhction. This detector has similarities to the locally optimum detector for comjposite signals in additive noise. The asymptotic performance of this nonparametric detector is shown to be as good as that of the locally optimum detector.

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곱셈꼴 잡음모형에서 비모수 확률 신호 검파기 (A nonparametric detector for random signals in a multiplicative noise model)

  • 배진수;박정순;김광순;송익호
    • 한국통신학회논문지
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    • 제23권4호
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    • pp.796-804
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    • 1998
  • 이동통신 시스템을 분석할 때 중요한 여러길 전파를 모형화하는 데에는 곱셈꼴 잡음이 쓸모있다고 알려져 있다. 이 논문에서는 곱셈꼴 잡음에서 약한 신호의 비모수 검파를 생각한다. 관측값의 부호와 순위를 바탕으로 한국소최적 검파기는 어떤 잡음 분포에서도 신호의 세기가 약할 때 이를 검파하는 성능이 좋도록 한 것이다. 이 검파기는 곱셈꼴 잡음에서 확률 신호를 검파하는 국소최적 검파기와 비슷하다는 것을 보인다. 그리고, 이 비모수 검파기는 국소최적 검파기와 점근적으로 거의 같은 성능을 갖는다는 것을 보인다.

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Using Change-Point Detection Tests to detect the Korea Economic Crisis of 1997

  • 오경주
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2004년도 추계학술대회
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    • pp.25-32
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    • 2004
  • In this study, we use various change-point detection methods to detects Korea economic crisis of 1997, and then compares their performance. In change-point detection method, there are three major categories: (1) the parametric approach, (2) the nonparametric approach, and (3) the model-based approach. Through the application to Korea foreign exchange rate during her economic crisis, we compare the employed change-point detection methods and, furthermore, determine which of them performs better.

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Comparing Change-Point Detection Methods to Detect the Korea Economic Crisis of 1997

  • Oh, Kyong-Joo
    • Journal of the Korean Data and Information Science Society
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    • 제15권3호
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    • pp.585-592
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    • 2004
  • This study detects Korea economic crisis of 1997 using various change-point detection methods and then compares their performance. In change-point detection method, there are three major categories: (1) the parametric approach, (2) the nonparametric approach, and (3) the model-based approach. Through the application to Korea foreign exchange rate during her economic crisis, we compare the employed change-point detection methods and, furthermore, determine which of them performs better.

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수질자료의 추세분석을 위한 비모수적 통계검정에 관한 연구 (A Study of Non-parametric Statistical Tests to Analyze Trend in Water Quality Data)

  • 이상훈
    • 환경영향평가
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    • 제4권2호
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    • pp.93-103
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    • 1995
  • This study was carried out to suggest the best statistical test to analyze the trend in monthly water quality data. Traditional parametric tests such as t-test and regression analysis are based on the assumption that the underlying population has a normal distribution and regression analysis additionally assumes that residual errors are independent. Analyzing 9-years monthly COD data collected at Paldang in Han River, the underlying population was found to be neither normal nor independent. Therefore parametric tests are invalid for trend detection. Four Kinds of nonparametric statistical tests, such as Run Test, Daniel test, Mann-Kendall test, and Time Series Residual Analysis were applied to analyze the trend in the COD data, Daniel test and Mann-Kendall test indicated upward trend in COD data. The best nonparametric test was suggested to be Daniel test, which is simple in computation and easy to understand the intuitive meaning.

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Estimation of Jump Points in Nonparametric Regression

  • Park, Dong-Ryeon
    • Communications for Statistical Applications and Methods
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    • 제15권6호
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    • pp.899-908
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    • 2008
  • If the regression function has jump points, nonparametric estimation method based on local smoothing is not statistically consistent. Therefore, when we estimate regression function, it is quite important to know whether it is reasonable to assume that regression function is continuous. If the regression function appears to have jump points, then we should estimate first the location of jump points. In this paper, we propose a procedure which can do both the testing hypothesis of discontinuity of regression function and the estimation of the number and the location of jump points simultaneously. The performance of the proposed method is evaluated through a simulation study. We also apply the procedure to real data sets as examples.

PRELIMINARY DETECTION FOR ARCH-TYPE HETEROSCEDASTICITY IN A NONPARAMETRIC TIME SERIES REGRESSION MODEL

  • HWANG S. Y.;PARK CHEOLYONG;KIM TAE YOON;PARK BYEONG U.;LEE Y. K.
    • Journal of the Korean Statistical Society
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    • 제34권2호
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    • pp.161-172
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    • 2005
  • In this paper a nonparametric method is proposed for detecting conditionally heteroscedastic errors in a nonparametric time series regression model where the observation points are equally spaced on [0,1]. It turns out that the first-order sample autocorrelation of the squared residuals from the kernel regression estimates provides essential information. Illustrative simulation study is presented for diverse errors such as ARCH(1), GARCH(1,1) and threshold-ARCH(1) models.

Using Artificial Neural Networks to detect Variance Change Point for Data Separation

  • 한영철;오경주;김태윤
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
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    • pp.1214-1220
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    • 2006
  • In this article, it will be shown that a nonparametric and data-adaptive approach to the variance change point (VCP) detection problem is possible by formulating it as a pattern classification problem. Technical aspects of the VCP detector are discussed, which include its training strategy and selection of proper classification tool.

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